Apoptosis is a genetically programmed cell death and its deregulation is associated among other pathologies, with cancer. While apoptosis is known to rely on the Bcl-2 family members and caspases, data suggest that two major families of serine/threonine phosphatases, PP1 and PP2A, are key actors involved in cell life or cell death decision. The Ser/Thre phosphatase PP2A has been implicated in both induction and prevention of apoptosis, pointing to a complex interplay of phosphatase actions. PP2A was shown to interact with caspase-9 through a particular sequence from the C-terminal portion of caspase-9. This sequence was identified as being YVETLDGIFEQWAHSEDL (SEQ ID NO: 1 for human caspase-9. This binding domain to PP2Ac corresponds to amino acid positions 363-380 of human caspase-9 (NCBI accession number NP 001 220) and is described in international patent application WO2010/112471. The counterpart sequence from the human PP2Ac subunit which interacts with its partner caspase-9 was then identified as being DTLDHIRALDRLQEVPHEGP (SEQ ID NO: 2), positions 175-194 of human PPA2c sequence (Swiss-Prot accession number P67775-1), as described in international patent application WO2012/042038. These interaction motifs between caspase 9 and PP2A have been proposed as pro-apoptotic peptides, and have proved very promising, in particular when fused to cell penetrating peptides.
As the choices of treatment for cancer have expanded, the need to identify predictive biomarkers to tailor treatment strategies to individual tumor has become necessary. Such strategies have the potential of maximizing antitumor effect while minimizing toxicity and improving clinical benefit. Advances in molecular therapeutics in the past decades have opened up possibilities for treating cancer patients with personalized therapies.
Some examples of predictive biomarkers being used in the daily clinical oncology practice are estrogen and progesterone receptors to predict sensitivity to endocrine therapy in breast cancer, HER2 to predict sensitivity to Herceptin treatment and KRAS mutation to predict resistance to EGFR antibody therapy. Such signatures predicting anti-cancer therapy response a priori or early in treatment enable an evidence-based decision making on available treatment options.
Similarly, there is a need for methods of predicting whether a patient would respond or not to a treatment with pro-apoptotic peptides.